A Kalman filter may be used to solve for static and dynamic parameters in a dynamic system having noisy measurements. One such system is a Global Navigation Satellite System (GNSS), in which satellite navigation measurements by navigation receivers (e.g., receivers on or near the surface of Earth) are affected by several sources of noise (e.g., multipath effects, ionospheric effects, tropospheric effects, etc.).
One application of Kalman filters is a Kalman filter (e.g., in a “wide area differential GPS (WADGPS) system) that tracks the orbits of thirty global navigation satellites using a set of reference stations (e.g., 50 to 80 reference stations) located around the world. The resulting orbital solutions are compared with the “almanac” data locations and trajectories of the satellites (herein after called almanac data), combined with the ephemeris information broadcast by the satellites or other systems, that provide navigation receivers with adjustments to the almanac data. The difference between the orbital solutions produced by the Kalman filter and the adjusted almanac data is used to generate correction information, sometimes called aiding data or differential data, that is broadcast to subscribers' navigation receivers (e.g., navigation receivers whose owners have paid a subscription fee). StarFire, a system and service provided by NavCom Technology, Inc., is an example of a system that tracks the orbits of global navigation satellites and transmits correction information to subscribers' navigation receivers. The differential data, when used by compatible navigation receivers, enables those receivers to more accurately determine their position, in some implementations with an accuracy of better than one meter.
It would be highly desirable to provide a system and method that determines improved correction information so as to enable navigation receivers to achieve higher levels of accuracy.